Relationship matching of data sources: A graph-based approach
| Autor: | Markus Stumptner, Georg Grossmann, Wolfgang Mayer, Wangyu Huang, Zaiwen Feng |
|---|---|
| Přispěvatelé: | Feng, Zaiwen, Mayer, Wolfgang, Stumptner, Marcus, Grossmann, Georg, Huang, Wangyu, 30th International Conference on Advanced Information Systems Engineering, CAiSE 2018 Tallinn, Estonia 11-15 June 2018 |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Matching (statistics)
semantic label Relational database Computer science 010401 analytical chemistry Process (computing) 020207 software engineering 02 engineering and technology Linked data linked data computer.software_genre semantic relation 01 natural sciences 0104 chemical sciences Data set Identification (information) knowledge graph 0202 electrical engineering electronic engineering information engineering Key (cryptography) Data mining computer Complement (set theory) |
| Zdroj: | Advanced Information Systems Engineering ISBN: 9783319915623 CAiSE |
| Popis: | Relationship matching is a key procedure during the process of transforming structural data sources, like relational data bases, spreadsheets into the common data model. The matching task refers to the automatic identification of correspondences between relationships of source columns and the relationships of the common data model. Numerous techniques have been developed for this purpose. However, the work is missing to recognize relationship types between entities in information obtained from data sources in instance level and resolve ambiguities. In this paper, we develop a method for resolving ambiguous relationship types between entity instances in structured data. The proposed method can be used as standalone matching techniques or to complement existing relationship matching techniques of data sources. The result of an evaluation on a large real-world data set demonstrated the high accuracy of our approach (>80%). Refereed/Peer-reviewed |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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